Comparing and aggregating rankings with ties

作者: Ronald Fagin , Ravi Kumar , Mohammad Mahdian , D. Sivakumar , Erik Vee

DOI: 10.1145/1055558.1055568

关键词:

摘要: Rank aggregation has recently been proposed as a useful abstraction that several applications, including meta-search, synthesizing rank functions from multiple indices, similarity search, and classification. In database applications (catalog searches, fielded parametric etc.), the rankings are produced by sorting an underlying according to various fields. Typically, there number of fields each have very few distinct values, hence corresponding many ties in them. Known methods for poorly suited this context, difficulties can be traced back fact we do not sound mathematical principles compare two partial rankings, is, allow ties.In work, provide comprehensive picture how We propose metrics present algorithms efficiently compute them, prove they within constant multiples other. Based on these concepts, formulate problems develop highly efficient algorithm top elements near-optimal rankings. model access is suitable databases, our reads essentially ranking necessary determine winner(s).

参考文章(20)
John D. Lafferty, Guy Lebanon, Cranking: Combining Rankings Using Conditional Probability Models on Permutations international conference on machine learning. pp. 363- 370 ,(2002)
Persi Diaconis, R. L. Graham, Spearman's Footrule as a Measure of Disarray Journal of the Royal Statistical Society: Series B (Methodological). ,vol. 39, pp. 262- 268 ,(1977) , 10.1111/J.2517-6161.1977.TB01624.X
M. G. KENDALL, THE TREATMENT OF TIES IN RANKING PROBLEMS Biometrika. ,vol. 33, pp. 239- 251 ,(1945) , 10.1093/BIOMET/33.3.239
Javed A. Aslam, Mark Montague, Models for metasearch international acm sigir conference on research and development in information retrieval. pp. 276- 284 ,(2001) , 10.1145/383952.384007
Ronald Fagin, D. Sivakumar, Ravi Kumar, Comparing top k lists symposium on discrete algorithms. ,vol. 17, pp. 28- 36 ,(2003) , 10.5555/644108.644113
M. Elena Renda, Umberto Straccia, Web metasearch Proceedings of the 2003 ACM symposium on Applied computing - SAC '03. pp. 841- 846 ,(2003) , 10.1145/952532.952698
R. R. Yager, V. Kreinovich, On How to Merge Sorted Lists Coming from Different Web Search Tools soft computing. ,vol. 3, pp. 83- 88 ,(1999) , 10.1007/S005000050056
Cynthia Dwork, Ravi Kumar, Moni Naor, D. Sivakumar, Rank aggregation methods for the Web Proceedings of the tenth international conference on World Wide Web - WWW '01. pp. 613- 622 ,(2001) , 10.1145/371920.372165
Maurice G. Kendall, Rank correlation methods ,(1948)